Taking Research and Development to the Clinic: Issues for Physicians

1. Taking Research and Development to the Clinic: Issues for Physicians AAAS/FDLI Colloquium I Diagnostics and Diagnoses Paths to Personalized Medicine Howard Levy, MD, PhD Johns Hopkins University June 1, 2009

2. What is Personalized Medicine? • Biomarkers and genetic tests • Customization of medical care to the individual patient • All aspects of care—not just biomarkers, not just genetics

3. Challenges & Opportunities Self-evident truths: • Physicians want to help patients • Time & resources are scarce Can biomarkers improve both?

4. Select a test Order a test Get it paid for Get it done Receive result Understand result Archive result Access result (now & future) Apply result in clinical care Using a Biomarker

5. Clinical Utility Does the biomarker improve clinical care? • Pharmacogenetics • Predictive testing • Faster or more precise diagnostics

6. Clinical Utility What are the costs? • Financial • Time/Resources • Social/Ethical/Legal • Medical (incorrect conclusions) • Psychological

7. The right drug At the right time In the right dose ↑ Efficacy ↓ Adverse events Pharmacogenetics

8. Warfarin Dosing • Fixed-dose • Clinical algorithm (weight, age, sex) • This is personalized medicine! • Pharmacogenetic (VKORC1 & CYP2C9) • PGx explains ~40% of dose variability • Clinical + PGx explains ~54% of variability

9. Int’l Warfarin PGx Consortium N Engl J Med 360(8):753-764 February 19, 2009

10. Warfarin PGx Clinical Utility • Likely to achieve therapeutic dose faster • Relatively easy to order & receive results • Often covered by 3rd parties • Algorithm freely available • Improved efficacy & fewer adverse events? • Seems likely • Still being studied

11. Warfarin PGx Clinical Utility Limitations: • Needs to be done promptly at initiation of therapy • ~45% of dose variability unexplained • Environmental factors remain important

12. Drug Metabolism: CYP450 • >50% of all drugs • Prodrug  Active Drug • Active  Inactive • Relevant Factors: • Other drugs • Diet & environment • Genetic variants

13. CYP450 PGx Clinical Utility • Genetic testing is available • Is PGx testing better than trial & error? • Drug choice & dosing recommendations? • What if there are no alternatives? • Psychological distress • Relative risk • Genetic determinism

14. Genetic Determinism Belief that clinical outcomes are inexorably defined by genetic factors Ignores: • Genetic/epigenetic modifiers • Environmental modifiers • Variable expression • Reduced penetrance

15. Predictive Testing “It’s tough to make predictions, especially about the future” -Dan Quayle, Casey Stengel, et al. “The future ain’t what it used to be” -Yogi Berra

16. Genetic Risk Assessment • Family History • Varies over time • DNA variants • Stable over time • Relative risk

17. GWAS: Genome-Wide Association Studies • Really BIG case-control study • 1000’s of subjects • 500,000 to 1,000,000 SNPs • Power to detect small effect sizes • Subject to same errors & biases as any other epidemiologic study

18. CAD Risk Assessment:Gene ↔ Environment • Smoking, HTN, DM, etc: OR ≈ 10-20 • SNPs: OR ≈ 1.2-2.0 (usually 1.2-1.3) • Family History: intermediate

19. Heritability • Proportion of disease predispositionthat is due to inherited factors • SNPs—small amount • Other heritable factors (DNA & Non-DNA variants) • Current tests assess only a small portion of heritability

20. Analytical & Clinical Validity • Is the test accurate? • Does the biomarker correlate clinically (retrospective vs. prospective study)? • How are results of multiple tests combined? • Validity is often assumed when test is offered clinically.

21. The Fallacy of Genetic Determinism Positive tests ≠ Disease Negative tests ≠ Health

22. Clinical Utility of Genetic Testing for Common Disease? • What do the results mean? • Small effect size • Environmental factors • Fallacy of genetic determinism • Undue anxiety/false reassurance?

23. Clinical Utility of Genetic Testing for Common Disease? • Modify therapy to reduce risk? • Motivation to change behavior? • Smoking, exercise & diet campaigns • Does the Personalized Medicine model work?

24. Clinical Utility of Genetic Testing for Common Disease? • Cost • Large amounts of clinical data • Paucity of tools to integrate data • Uncertain plan of action • May be appropriate for some patients

25. PM Opportunities • Improved diagnostics • Improved therapeutics • Improved health maintenance • More efficient use of time • Lower health care costs • Patient & physician satisfaction

26. PM Challenges Clinician Education • Test indications • Test validity • Result interpretation • Clinical utility • Integration into clinical care

27. Clinician Education Learning Preferences • Clinically relevant • Just in time (point of care) • Fast (<2 minutes) • Increasingly Internet-based • 2o sources (authority vs. accuracy) • GeneFacts

28. PM Challenges Test Validity • Transparency • Providers lack time & knowledge to evaluate • Regulation • Slows progress, limits access, ↑ cost • Paternalism vs. Autonomy

29. PM Challenges Test Ordering & Payment • Facilitating ordering the correct test • DTC testing vs. physician gatekeeper • 3rd party payers • Paternalism vs. Autonomy

30. PM Challenges Receiving, Archiving and Accessing Results • EHRs • Can also prompt provider to order/use tests • PHRs • Information sharing between providers • Does the data already exist? • Privacy & Security

31. PM Challenges Clinical Utility • Better assessment of health factors • Genetic • Environmental • Better tools to combine environment, family history & biomarkers • Studies of actual clinical outcomes (Hype  Hope  Reality)

32. The Art of Medicine • Evidence-based medicine • Based on population studies • Individual people • Autonomous • Variably reliable • Ever-changing environment • Personalized Medicine • Requires knowing & monitoring the patient and therapy at the individual level